Intro to List Comprehensions in Python (lightning talk)
Other Topics Available
Data Science/Machine Learning
Applications of GPU (single or cluster) for deep learning (PyTorch or Tensorflow/Keras)
Using Dask to parallelize machine learning
Industry specific applications, such as IIOT, Education, and Hospitality
Data science team collaboration strategies
Cloud Based Machine Learning - putting your workflow in the cloud from end to end
Deploying ML Models into Flask or Voila (hands-on)
Data Engineering/Programming
Specific data storage technologies: Redshift, PostgreSQL, Elasticsearch
Machine learning production workflows using AWS Redshift and Airflow
Developing/distributing packages in R or Python
Parallelization for Python: Intro to Dask (30-45 min, can be hands-on)
R Functions Workshop (2 hours with hands-on)
Data Visualization
R: ggplot, shiny, plotly, gganimate
Python: plotnine, bokeh, plotly, altair
GIS or Network Graphs
Sociological insights on data science, machine learning, and/or AI
Democratization of GPU access for machine learning (30-45 min)
Requirements
Aside from my equity and diversity requirements noted below, I’d ask that you give the following information when requesting my presence at an event.
Speaker compensation policies, if any. for community or nonprofit organizations, I am usually happy to speak without compensation. For other organizations, I am happy to negotiate a speaking fee that is within the reach of your budget.
Location. I am available to travel for talks as appropriate, but am always free to do remote talks as well.
Event theme and content area. It helps me to choose the right topic and angle on the topic to present, and to decide whether I am a good fit for your event.
The size and general makeup of the audience you expect. I tailor each talk to the audience and event, and so I would like to know what sort of data science expertise and demographics you hope to have. This can be an estimate.
Date/time of event if already scheduled. If you have a flexible calendar, then we can just discuss this and come to a mutual agreement.
Diversity and Equity
I believe that our personal values should be reflected in our work, so I don’t participate in events where I am the only woman, events with one or fewer people of color on the speaking schedule, or events organized by groups that don’t explicitly support equal opportunity and require respectful conduct from attendees.
There is an abundance of extremely talented women, people of color, and LGBT+ people in the data science industry, and if you are struggling to find them for your event or job opening, please let me know and I may be able to help connect you.